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Personal profile

Education/Academic qualification

PHD, University of Iowa

… → 2001

MS, Beijing University of Aeronautics and Astronautics

… → 1995

BS, Beijing University of Aeronautics and Astronautics

… → 1992

Fingerprint Dive into the research topics where Teresa Wu is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Supply chains Engineering & Materials Science
Magnetic Resonance Imaging Medicine & Life Sciences
Ambulances Engineering & Materials Science
Brain Engineering & Materials Science
Concurrent engineering Engineering & Materials Science
Imaging techniques Engineering & Materials Science
Tomography Engineering & Materials Science
Supply chain management Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 1999 2019

A dual-mode deep transfer learning (D2TL) system for breast cancer detection using contrast enhanced digital mammograms

Wang, K., Patel, B. K., Wang, L., Wu, T., Zheng, B. & Li, J., Jan 1 2019, In : IISE Transactions on Healthcare Systems Engineering.

Research output: Contribution to journalArticle

Mammography
Learning systems
cancer
Breast Neoplasms
diagnostic

An effective and robust decomposition-ensemble energy price forecasting paradigm with local linear prediction

Qin, Q., Xie, K., He, H., Li, L., Chu, X., Wei, Y. M. & Wu, T., Sep 1 2019, In : Energy Economics. 83, p. 402-414 13 p.

Research output: Contribution to journalArticle

Natural Gas
Time series
Natural gas
Signal processing
Decomposition

Deep Residual Inception Encoder-Decoder Network for Medical Imaging Synthesis

Gao, F., Wu, T., Chu, X., Yoon, H., Xu, Y. & Patel, B., Jan 1 2019, In : IEEE Journal of Biomedical and Health Informatics.

Research output: Contribution to journalArticle

Medical imaging
Diagnostic Imaging
Neuroimaging
Neural networks
Precision Medicine

ENTRNA: A framework to predict RNA foldability

Su, C., Weir, J. D., Zhang, F., Yan, H. & Wu, T., Jul 3 2019, In : BMC bioinformatics. 20, 1, 373.

Research output: Contribution to journalArticle

Open Access
RNA
Predict
Folding
Structure Prediction
Data-driven

Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI

Gaw, N., Hawkins-Daarud, A., Hu, L. S., Yoon, H., Wang, L., Xu, Y., Jackson, P. R., Singleton, K. W., Baxter, L. C., Eschbacher, J., Gonzales, A., Nespodzany, A., Smith, K., Nakaji, P., Mitchell, J. R., Wu, T., Swanson, K. R. & Li, J., Dec 1 2019, In : Scientific reports. 9, 1, 10063.

Research output: Contribution to journalArticle

Open Access
Glioblastoma
Cell Count
Magnetic Resonance Imaging
Neoplasms
Machine Learning

Projects 2003 2022